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Rhetorical Questions in LLM Representations: A Linear Probing Study ASTER: Latent Pseudo-Anomaly Generation for Unsupervised Time-Series Anomaly Detection Three Roles, One Model: Role Orchestration at Inference Time to Close the Performance Gap Between Small and Large Agents Variance Computation for Weighted Model Counting with Knowledge Compilation Approach FCBV-Net: Category-Level Robotic Garment Smoothing via Feature-Conditioned Bimanual Value Prediction
AI RESEARCH

Rhetorical Questions in LLM Representations: A Linear Probing Study

April 17, 2026 Admin
AI RESEARCH

ASTER: Latent Pseudo-Anomaly Generation for Unsupervised Time-Series Anomaly Detection

April 17, 2026 Admin
AI RESEARCH

Three Roles, One Model: Role Orchestration at Inference Time to Close the Performance Gap Between Small and Large Agents

April 17, 2026 Admin
AI RESEARCH

Variance Computation for Weighted Model Counting with Knowledge Compilation Approach

April 17, 2026 Admin
AI RESEARCH

FCBV-Net: Category-Level Robotic Garment Smoothing via Feature-Conditioned Bimanual Value Prediction

April 17, 2026 Admin
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Rhetorical Questions in LLM Representations: A Linear Probing Study
AI RESEARCH
Rhetorical Questions in LLM Representations: A Linear Probing Study
ASTER: Latent Pseudo-Anomaly Generation for Unsupervised Time-Series Anomaly Detection
AI RESEARCH
ASTER: Latent Pseudo-Anomaly Generation for Unsupervised Time-Series Anomaly Detection
Three Roles, One Model: Role Orchestration at Inference Time to Close the Performance Gap Between Small and Large Agents
AI RESEARCH
Three Roles, One Model: Role Orchestration at Inference Time to Close the Performance Gap Between Small and Large Agents
Variance Computation for Weighted Model Counting with Knowledge Compilation Approach
AI RESEARCH
Variance Computation for Weighted Model Counting with Knowledge Compilation Approach
AI Education: How to Get Ahead in the 21st Century Job Market!
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AI Education: How to Get Ahead in the 21st Century Job Market!
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The Power of NLP: How to Transform Text into Actionable Insights!
The AI Breakthrough That Could Change the World!
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Mastering NLP: How to Use Language to Your Advantage in the Digital Age!
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Rhetorical Questions in LLM Representations: A Linear Probing Study
AI RESEARCH
Rhetorical Questions in LLM Representations: A Linear Probing Study
ASTER: Latent Pseudo-Anomaly Generation for Unsupervised Time-Series Anomaly Detection
AI RESEARCH
ASTER: Latent Pseudo-Anomaly Generation for Unsupervised Time-Series Anomaly Detection
Three Roles, One Model: Role Orchestration at Inference Time to Close the Performance Gap Between Small and Large Agents
AI RESEARCH
Three Roles, One Model: Role Orchestration at Inference Time to Close the Performance Gap Between Small and Large Agents
Variance Computation for Weighted Model Counting with Knowledge Compilation Approach
AI RESEARCH
Variance Computation for Weighted Model Counting with Knowledge Compilation Approach
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Unlock the Power of Machine Learning: Learn the Techniques that are Revolutionizing Industry!

April 9, 2023 Admin

Machine Learning is transforming the world as we know it. From improving healthcare to predicting market trends, this innovative technology…

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The Future Is Here: The Latest News And Developments In The World Of AI!

April 9, 2023 Admin

Artificial intelligence (AI) is rapidly evolving, and it is becoming an integral part of our daily lives. From business to…

AI RESEARCH

Rhetorical Questions in LLM Representations: A Linear Probing Study

April 17, 2026 Admin

arXiv:2604.14128v1 Announce Type: cross Abstract: Rhetorical questions are asked not to seek information but to persuade or signal stance. How…

AI RESEARCH

ASTER: Latent Pseudo-Anomaly Generation for Unsupervised Time-Series Anomaly Detection

April 17, 2026 Admin

arXiv:2604.13924v1 Announce Type: cross Abstract: Time-series anomaly detection (TSAD) is critical in domains such as industrial monitoring, healthcare, and cybersecurity,…

AI RESEARCH

Three Roles, One Model: Role Orchestration at Inference Time to Close the Performance Gap Between Small and Large Agents

April 17, 2026 Admin

arXiv:2604.11465v2 Announce Type: replace Abstract: Large language model (LLM) agents show promise on realistic tool-use tasks, but deploying capable agents…

AI RESEARCH

Variance Computation for Weighted Model Counting with Knowledge Compilation Approach

April 17, 2026 Admin

arXiv:2601.03523v2 Announce Type: replace Abstract: One of the most important queries in knowledge compilation is weighted model counting (WMC), which…

AI RESEARCH

FCBV-Net: Category-Level Robotic Garment Smoothing via Feature-Conditioned Bimanual Value Prediction

April 17, 2026 Admin

arXiv:2508.05153v2 Announce Type: replace-cross Abstract: Category-level generalization for robotic garment manipulation, such as bimanual smoothing, remains a significant hurdle due…

AI RESEARCH

Exploration and Exploitation Errors Are Measurable for Language Model Agents

April 17, 2026 Admin

arXiv:2604.13151v1 Announce Type: new Abstract: Language Model (LM) agents are increasingly used in complex open-ended decision-making tasks, from AI coding…

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Rethinking On-Policy Distillation of Large Language Models: Phenomenology, Mechanism, and Recipe

April 17, 2026 Admin

arXiv:2604.13016v2 Announce Type: replace-cross Abstract: On-policy distillation (OPD) has become a core technique in the post-training of large language models,…

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Beyond Conservative Automated Driving in Multi-Agent Scenarios via Coupled Model Predictive Control and Deep Reinforcement Learning

April 17, 2026 Admin

arXiv:2604.13891v1 Announce Type: cross Abstract: Automated driving at unsignalized intersections is challenging due to complex multi-vehicle interactions and the need…

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Evaluating Supervised Machine Learning Models: Principles, Pitfalls, and Metric Selection

April 17, 2026 Admin

arXiv:2604.13882v1 Announce Type: cross Abstract: The evaluation of supervised machine learning models is a critical stage in the development of…

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CodeTracer: Towards Traceable Agent States

April 17, 2026 Admin

arXiv:2604.11641v3 Announce Type: replace-cross Abstract: Code agents are advancing rapidly, but debugging them is becoming increasingly difficult. As frameworks orchestrate…

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AI RESEARCH

Rhetorical Questions in LLM Representations: A Linear Probing Study

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